Computer aided drug design using virtual screening and molecular energy calculation of a specific neurodegenerative diseases

  • Abstract
  • Keywords
  • References
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  • Abstract

    Computer-aided drug design (CADD) is designing a drug with the help of computational algorithms. Information technology advances to creates the structure of molecules, molecular modeling and calculate the binding energies of the drug to initiate a new medicine against neurodegenerative diseases. In our work, we implemented virtual screening of a drug-protein interaction is selected from drug data bank with potential drug bank inhibitory activity for a specific neurodegenerative disease. Here we analyze technical CADD studies of the neurodegenerative diseases. Finally selecting the best alkaloid for a specific neurodegenerative disease and predicting the efficiency using computation of alkaloid with molecular energy.

  • Keywords

    Computer Aided Drug Design; Neurodegenerative Diseases; Virtual Screening; Molecular Energy Calculation.

  • References

      [1] Nair, B. B., Bhaskaran, V., &Arunjit, K. (2017). Structural designing of suppressors for autisms spectrum diseases using molecular dynamics sketch. International Journal of Drug Delivery, 8(4), 142-146.

      [2] Azam, F., Mohamed, N., &Alhussen, F. (2015). Molecular interaction studies of green tea catechins as multitarget drug candidates for the treatment of Parkinson’s disease: computational and structural insights. Network: Computation in Neural Systems, 26(3-4), 97-115.

      [3] Scotti, L., & Tullius Scotti, M. (2015). Computer aided drug design studies in the discovery of secondary metabolites targeted against age-related neurodegenerative diseases. Current topics in medicinal chemistry, 15(21), 2239-2252.

      [4] Zeng, H., & Wu, X. (2016). Alzheimer's disease drug development based on Computer-Aided Drug Design. European journal of medicinal chemistry, 121, 851-863.

      [5] Robinson, M., Lee, B. Y., &Leonenko, Z. (2017). Drugs and Drug Delivery Systems Targeting Amyloid-b {eta} in Alzheimers Disease. arXiv preprint arXiv:1704.08313.

      [6] Ahmad, K., M Balaramnavar, V., H Baig, M., K Srivastava, A., Khan, S., & A Kamal, M. (2014). Identification of potent caspase-3 inhibitors for treatment of multi-neurodegenerative diseases using pharmacophore modeling and docking approaches. CNS & Neurological Disorders-Drug Targets (Formerly Current Drug Targets-CNS & Neurological Disorders), 13(8), 1346-1353.

      [7] Vangavaragu, J. R., Valasani, K. R., Gan, X., & Yan, S. S. (2014). Identification of human presequence protease (hPreP) agonists for the treatment of Alzheimer's disease. European journal of medicinal chemistry, 76, 506-516.

      [8] da Cunha, E. F., Resende, J. E., Franca, T. C., Gonçalves, M. A., de Souza, F. R., Santos-Garcia, L., &Ramalho, T. C. (2013). Molecular modeling studies of piperidine derivatives as new acetylcholinesterase inhibitors against neurodegenerative diseases. Journal of Chemistry, 2013.

      [9] Jayaraj, R. L., Ranjani, V., Manigandan, K., &Elangovan, N. (2013). Insilico docking studies to identify potent inhibitors of alpha-synuclein aggregation in Parkinson Disease. Asian J Pharm Clin Res, 6(4), 127-131.

      [10] Sarkar, A., Kumar, S., Grover, A., &Sundar, D. (2012). Protein aggregation in neurodegenerative diseases: Insights from computational analyses. Current Bioinformatics, 7(1), 87-95.

      [11] Chen, C. Y. C. (2012). Mechanism of BAG1 repair on Parkinson’s disease-linked DJ1 mutation. Journal of Biomolecular Structure and Dynamics, 30(1), 1-12.

      [12] Y Wong, K., R Duchowicz, P., G Mercader, A., & A Castro, E. (2012). QSAR applications during last decade on inhibitors of acetylcholinesterase in Alzheimer's disease. Mini reviews in medicinal chemistry, 12(10), 936-946.

      [13] Nastase, A. F., & Boyd, D. B. (2012). Simple structure-based approach for predicting the activity of inhibitors of beta-secretase (BACE1) associated with Alzheimer’s disease. Journal of chemical information and modeling, 52(12), 3302-3307.

      [14] Namboori, P. K., Vineeth, K. V., Rohith, V., Hassan, I., Sekhar, L., Sekhar, A., &Nidheesh, M. (2011). The ApoE gene of Alzheimer's disease (AD). Functional & integrative genomics, 11(4), 519-522.

      [15] Kumar, S., Shilpa, S., Anil Kumar, N. C., Rohith, V., & PK, K. N. (2010). Characterization of Microsatellite Regions of the Genes Causing ‘Alzheimer’s Disease’. Int. J. of Recent Trends in Engineering and Technology, 4(2).

      [16] Rigamonti, D., Mutti, C., Zuccato, C., Cattaneo, E., &Contini, A. (2009). Turning REST/NRSF dysfunction in Huntington's disease into a pharmaceutical target. Current pharmaceutical design, 15(34), 3958-3967.

      [17] Avram, S., Milac, A. L., Mihailescu, D. F., Dabu, A., &Flonta, M. L. (2006). Computer-Aided Drug Design Applied to Beta and Gamma Secretase Inhibitors-Perspectives for New Alzheimer Disease Therapy. Current Enzyme Inhibition, 2(4), 311-328.

      [18] Zhang, H. Y. (2005). One‐compound‐multiple‐targets strategy to combat Alzheimer's disease. FEBS letters, 579(24), 5260-5264.

      [19] Youdim, M. B., &Buccafusco, J. J. (2005). Multi-functional drugs for various CNS targets in the treatment of neurodegenerative disorders. Trends in Pharmacological Sciences, 26(1), 27-35.

      [20] Recanatini, M., Cavalli, A., &Hansch, C. (1997). A comparative QSAR analysis of acetylcholinesterase inhibitors currently studied for the treatment of Alzheimer's disease. Chemico-biological interactions, 105(3), 199-228.




Article ID: 9751
DOI: 10.14419/ijet.v7i1.9.9751

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